Trish Whetzel

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Trish Whetzel

Trish Whetzel

@TrishWhetzel

Full Stack Web developer and ontologist working in bioinformatics https://t.co/MCrROWm5ka

Bay area, CA Katılım Eylül 2011
5.2K Takip Edilen3.3K Takipçiler
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Trish Whetzel
Trish Whetzel@TrishWhetzel·
I built KidSketch for the Gemini Live Agent Challenge - an AI agent that turns children's drawings into illustrated story movies #GeminiLiveAgentChallenge
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Rohit
Rohit@ai_rohitt·
🚨 Anthropic just showed a 24-minute workshop on how to actually do prompts for Claude. Taught by the people who built it. Free. No registration. No paywall. I've seen $300 courses that don't cover what they teach in the first 8 minutes. Watch it and bookmark it now.
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Google for Startups
Google for Startups@GoogleStartups·
Meet the 100+ pioneering startups joining the second Gemini Startup Forum. 🌎🛠 On June 16–17 at Google’s Sunnyvale HQ, these global founders will take part in an intensive, two-day summit designed to accelerate the global scale and impact of their AI solutions. Participants will collaborate directly with experts from across @Google to overcome technical hurdles, refine growth strategies, and scale their solutions globally using Google’s premier AI infrastructure. 🚀 Learn more about the cohort: goo.gle/48US2BM
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Trish Whetzel
Trish Whetzel@TrishWhetzel·
@rseroter Great, I see the Plan mode and am testing it out now for a simple web site. For "ask", yes to ask a specific question about line(s) of code or a general coding question. I use these modes often in Cursor and miss these in Antigravity.
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Richard Seroter
Richard Seroter@rseroter·
Google Antigravity beats Claude at coding—but only if you stop acting like a programmer howtogeek.com/google-antigra… < all these tools are great; just pick one. But regardless, don't bring your old approach to new tools.
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Google for Developers
Google for Developers@googledevs·
Calling all developers 📣 Sign up to participate in user research studies and influence how Google evolves the tools, APIs, and guidance for millions of people around the world. 🌎 Get started by telling us more about your development experience: goo.gle/4uPE4cU
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Google Cloud Tech
Google Cloud Tech@GoogleCloudTech·
Go beyond simple chatbots and build a distributed multi-agent system—this codelab will show you how → goo.gle/4udm8Jc Build the architecture needed to enable multiple agents to work together to achieve a shared goal.
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Richard Seroter
Richard Seroter@rseroter·
Forward Deployed Engineers shouldn't *be* your AI implementation strategy. But they can be an important piece. At @googlecloud, it's game on. The best in the biz is building out our team so we can help enterprises do AI well at scale. Apply! linkedin.com/posts/rarni_go…
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Trish Whetzel
Trish Whetzel@TrishWhetzel·
@googledevs Are these sessions presented by Google Dev Rel or community presentations by GDEs?
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Google for Developers
Google for Developers@googledevs·
Master the tools to build your own grounded AI companion with the experts who use them every day. Register 💻 → goo.gle/4npl2Hu Join our live AI Learning Labs for a hands-on deep dive into: 🔹 Gemini CLI & Python 🔹 Agent Grounding via Google Search 🔹 MCP Server & Agent ADK 🔹 Custom Avatar generation with Imagen Move past the basics and build a one-of-a-kind interactive agent with real-time support from Google Developer Experts. 📅 May 27-29
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Google for Developers
Google for Developers@googledevs·
Get @GoogleCloud certified. ☁️ Google Cloud customers can join GEAR to apply and access an up to 9-week cohort featuring technical mentorship and instructor-led training into various topics → goo.gle/4wqeCfF
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Suraj Sharma
Suraj Sharma@suraj_sharma14·
If I had 6 months to become an Applied AI Engineer. I’d do this. Stage 1: Python + Production APIs FastAPI, async, error handling, webhooks, REST/GraphQL, third-party SDKs. Stage 2: LLM Fundamentals for Production Tokens, context windows, model routing, embeddings, cost/latency tradeoffs. Stage 3: Prompt Engineering + Structured Outputs System prompts, few-shot chains, Pydantic/JSON validation, prompt versioning, unit evals. Stage 4: RAG + Knowledge Grounding Chunking strategies, hybrid search, rerankers, vector DBs, metadata filtering, citation tracking. Stage 5: AI Workflows + Orchestration Tool calling, state machines, human-in-the-loop, retry logic, fallback chains, session memory. Stage 6: Build Production-Ready Apps Domain-specific copilots, automation pipelines, streaming UIs, graceful degradation, rate limiting. Stage 7: Evaluation + Reliability Accuracy scoring, hallucination detection, RAGAS/DeepEval, regression testing, A/B output validation. Stage 8: AI Infrastructure + Optimization vLLM, Ollama, quantization, KV caching, response streaming, token cost tracking, edge deployment. Stage 9: Deployment + Observability Docker, CI/CD, cloud hosting, distributed tracing, structured logging, alerting, canary releases. Stage 10: AI Security + Guardrails Input/output filtering, prompt injection defense, PII redaction, compliance checks, sandboxing. Stage 11: Open Source + Portfolio Ship end-to-end apps publicly, write architecture docs, record demo walkthroughs, publish eval reports. Stage 12: Apply Applied AI Engineer, GenAI Developer, AI Integration Engineer, LLM Solutions roles. Most people stay stuck watching tutorials. Builders get hired.
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Logan Kilpatrick
Logan Kilpatrick@OfficialLoganK·
Come celebrate after Google IO with the DeepMind team in SF on May 21st :) Lots to look forward to!! Link in 🧵
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Richard Seroter
Richard Seroter@rseroter·
Choosing between APIs, MCP, and Agent-to-Agent architectures lakshmanok.medium.com/choosing-betwe… < @lak_luster says to default to function tools that use REST APIs, and only bring in MCP or A2A when there's more reasoning involved, or dynamic use cases.
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Google for Startups
Google for Startups@GoogleStartups·
The Google for Startups AI Agents Challenge is now LIVE. 🦾⚡️ Build autonomous systems with @GeminiApp and the recently upgraded Agent Development Kit for a chance to win a share of $90,000 and $500 in @GoogleCloud credits! Register now to start building: goo.gle/4cpi2pB
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Brij Pandey
Brij Pandey@LearnWithBrij·
Claude Code ships with 5 architectural layers most engineers never open. Not features. Not settings. Layers — each solving a distinct problem that LLMs alone can't solve. And four of them have nothing to do with prompting. Here's the full Agent Development Kit: Layer 1 — CLAUDE.md → The Memory Layer Architecture rules, naming conventions, test expectations, repo map. Always loaded. Always active. Two scopes: • ~/.claude/CLAUDE.md → global • .claude/CLAUDE.md → project This isn't context you paste in before every session. It's context that never needs repeating. The agent's constitution. Layer 2 — Skills → The Knowledge Layer Each SKILL.md carries a description. Claude matches it at runtime and forks the skill into an isolated subagent. On-demand, never always-on. Task-specific knowledge without inflating your main context window. Modular by design. Layer 3 — Hooks → The Guardrail Layer PreToolUse → PostToolUse → SessionStart → Stop → SubagentStop This is the layer most teams skip. And the one they regret skipping first. Hooks are NOT AI. They're deterministic event-driven shell commands. • Auto-lint on every Write • Hard-block on rm -rf • Slack notification on Stop Event fires → Matcher checks → Command runs Quality enforced at the infrastructure level. Not the prompt level. Layer 4 — Subagents → The Delegation Layer Each subagent gets its own context window, model, tools, and permissions. Main agent delegates down. Receives results up. That's it. No infinite recursion — subagents can't spawn subagents. Main context stays clean. Hard boundaries by design. Layer 5 — Plugins → The Distribution Layer Bundle your skills + agents + hooks + commands into a plugin. One install. Whole team inherits the behavior. Think npm packages — but for what your agent knows how to do. Wrapping everything: → MCP Servers on the left (GitHub, databases, APIs, custom integrations) → Agent Teams on the right (parallel execution, message passing, shared permissions) The 5-layer stack in one line: CLAUDE.md sets rules → Skills provide expertise → Hooks enforce quality → Subagents delegate work → Plugins distribute to the team Most production failures in agentic systems trace back to one missing layer. Which one is the gap in your current setup?
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Gemini CLI
Gemini CLI@geminicli·
Scion is a new multi-agent orchestration tool that orchestrates agents (Claude Code, Gemini CLI, Codex, and others) as isolated, concurrent processes. Each agent gets its own container, git worktree, and credentials — so they can work on different parts of your project without stepping on each other. github.com/GoogleCloudPla…
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👩‍💻 Paige Bailey
👩‍💻 Paige Bailey@DynamicWebPaige·
🪨 New @Kaggle competition (with a $50,000 prize!) just dropped, and it's near to my geophysicist heart: Drilling a horizontal well is like navigating underground without a map. The path forward runs through layers of rock you can’t see. Build models to predict the geology along a horizontal wellbore. Your work will help automate and improve drilling operations in the oil and gas industry.
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